Various modern media measurement and analytics solutions such as so-called mobile and Internet panels are typically utilized by the marketing firms, audience measurement professionals and hardware, application (app) or service vendors to characterize the behavior of the users of the supplied digital products through obtaining and analyzing the related usage data. The evident goal is to get grasp on the underlying trends, habits, problems and needs, whereupon better functioning and larger audience reaching products, more accurate marketing and obviously elevated business profit could ultimately emerge.
Many of the contemporary analytics tools seem to concentrate on tracking a number of relatively general technical indicators such as predetermined HTTP (Hypertext Transfer Protocol) events and e.g. active thread/application names, or exploiting application and/or platform-specific, highly tailored meters, which either limits the versatility of the obtainable data or complicates and slows down the development of the tools and related logic considerably as they have to be particularly tuned regarding each monitored product, respectively. Thus, so far the main approach to implement mobile and Internet tracking systems has been in monitoring certain specific indications of data traffic or the internal signals or states of the target entities, such as applications, during the usage thereof on mobile and Internet platforms.
However, the evolution of media and Internet services such as web sites or web-accessible services is now faster than ever. Both wired (e.g. computers and smart TVs) and wireless devices (e.g. tablets and smartphones) have already changed the way people access and engage with digital services, and as a result, both the business and technological landscapes are encountering constant turbulence. Further, user behavior is changing quickly due to, for instance, parallel use of multiple competent devices ranging from smartphones to tablets, and from laptops to smart TVs. Particularly in mobile context, consumers already have a choice from a library of over a million applications, or ‘apps’, available in the app stores, and they can opt to use not only native applications but also e.g. HTML5 (Hypertext Markup Language) applications, widgets, web sites, or something in between.
It is also very likely that at least in the near future we will see no stop or even interruption in the integration type trend of these devices and services concerning e.g. mobile payments, Internet-based transactions, authentication, m-commerce, e-commerce, coupons, next generation serendipity, NFC (Near-field Communication) based services, location-based services such as advertising, transactions with the physical world and divergence in UIs (user interface) in terms of e.g. smart goggles, multiple-screen devices and speech control. More and more devices, equipped with different screens and generally UIs, will enter the market and correspondingly, even a greater number of apps and features will become available to the general public.
The data resulting from the current data collection and mining tools is simply not adequate as to the growing demand for digital analytics and audience estimations.
There's thus a need for scalable media measurement solution capable of mobile and Internet measurements and adapting better to modern media environment arising from the increased complexity and fragmentation of the related devices, applications and services, thereby providing for a dynamic, high resolution scalable approach for mobile and Internet metering and analytics.
For example, both the markets considering e.g. hedge funds, portfolio analysts, and investment banks, and mobile/Internet industry players such as device vendors, carriers, app developers, and Internet companies all alike, would prefer obtaining substantially real-time insight on the actual use of Internet services—whether used through native apps, HTML5 software, web sites, or widgets.
Holistic projections of the digital audience, over the long-tail of properties, conducted e.g. on a daily basis, would undoubtedly be rather useful in supporting fact-based decisions, whether it is about investing into a stock, analyzing competition, or understanding consumer behaviors to gain new users, minimize churn or to increase user engagement, for instance. Instead of survey data or data on installations, on-device metered reach and engagement data on total and unduplicated usage could indeed be offered e.g. through a dynamic web reporting dashboard and integrated business intelligence tools, providing near real-time statistics and various options for users to extract relevant data cuts and correlations themselves, whenever they need it.